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PURPOSE: To characterize the recovery of diagnostic cardiovascular procedure volumes in U.S. and non-U.S. facilities in the year following the initial COVID-19 outbreak. MATERIALS AND METHODS: The International Atomic Energy Agency (IAEA) coordinated a worldwide study called the IAEA Noninvasive Cardiology Protocols Study of COVID-19 2 (INCAPS COVID 2), collecting data from 669 facilities in 107 countries, including 93 facilities in 34 U.S. states, to determine the impact of the pandemic on diagnostic cardiovascular procedure volumes. Participants reported volumes for each diagnostic imaging modality used at their facility for March 2019 (baseline), April 2020, and April 2021. This secondary analysis of INCAPS COVID 2 evaluated differences in changes in procedure volume between U.S. and non-U.S. facilities and among U.S. regions. Factors associated with return to prepandemic volumes in the United States were also analyzed in a multivariable regression analysis. RESULTS: Reduction in procedure volumes in April 2020 compared with baseline was similar for U.S. and non-U.S. facilities (-66% vs -71%, P = .27). U.S. facilities reported greater return to baseline in April 2021 than did all non-U.S. facilities (4% vs -6%, P = .008), but there was no evidence of a difference when comparing U.S. facilities with non-U.S. high-income country (NUHIC) facilities (4% vs 0%, P = .18). U.S. regional differences in return to baseline were observed between the Midwest (11%), Northeast (9%), South (1%), and West (-7%, P = .03), but no studied factors were significant predictors of 2021 change from prepandemic baseline. CONCLUSION: The reductions in cardiac testing during the early pandemic have recovered within a year to prepandemic baselines in the United States and NUHICs, while procedure volumes remain depressed in lower-income countries.Keywords: SPECT, Cardiac, Epidemiology, Angiography, CT Angiography, CT, Echocardiography, SPECT/CT, MR Imaging, Radionuclide Studies, COVID-19, Cardiovascular Imaging, Diagnostic Cardiovascular Procedure, Cardiovascular Disease, Cardiac Testing Supplemental material is available for this article. © RSNA, 2023.

A lot of lessons are learned post COVID-19 pandemic, including in the tourism business. Prior to the pandemic, tour operators had difficulties in competing with online travel agents (OTA) in terms of product sales and marketing. This article aims to understand the perception of digital marketing usage among tour operators and explore the factors influencing the adoption or rejection to it by using an integrated framework model which was grounded on the Unified Theory of Acceptance and Use of Technology (UTAUT). The factors identified which effect the usage of digital marketing technology were perceived ease of use, personal innovativeness, and facilitating condition, toward use behaviour. These factors were moderated by behaviour intention. The model was tested with 77 tour operator companies that are members of a travel agency association in Indonesia using PLS- SEM. The results show that tour operators’ facilitating condition and behaviour intention influence use behaviour directly. On the other hand, perceive ease of use, personal innovativeness, and facilitating condition directly influence behaviour intention. Personal innovativeness influences use behaviour mediated by behaviour intention. This study contributes to the understanding of tour operators where they need to focus on improving the ease of use and encouraging a positive intention among users.

Abstract Heart failure (HF) causes substantial morbidity and mortality but its pathobiology is incompletely understood. The proteome is a promising intermediate phenotype for discovery of novel mechanisms. We measured 4877 plasma proteins in 13,900 HF-free individuals across three analysis sets with diverse age, geography, and HF ascertainment to identify circulating proteins and protein networks associated with HF development. Parallel analyses in Atherosclerosis Risk in Communities study participants in mid-life and late-life and in Trøndelag Health Study participants identified 37 proteins consistently associated with incident HF independent of traditional risk factors. Mendelian randomization supported causal effects of 10 on HF, HF risk factors, or left ventricular size and function, including matricellular (e.g. SPON1, MFAP4), senescence-associated (FSTL3, IGFBP7), and inflammatory (SVEP1, CCL15, ITIH3) proteins. Protein co-regulation network analyses identified 5 modules associated with HF risk, two of which were influenced by genetic variants that implicated trans hotspots within the VTN and CFH genes.

Background: The COVID-19 pandemic disproportionately impacted Latin America (LATAM), significantly disrupting cardiovascular testing. This study evaluated cardiac procedure recovery in LATAM one year after the outbreak. Methods: The International Atomic Energy Agency (IAEA) surveyed 669 centers in 107 countries worldwide, including 135 facilities in 19 LATAM countries, to assess cardiovascular procedure volumes in March 2019, April 2020, and April 2021, and changes in center practices and staffing conditions one year into the COVID-19 pandemic. Findings: LATAM centers reported a 21 % decrease in procedure volumes in April 2021 from pre-pandemic-baseline, vs. a 0 % change in the rest of the world (RoW), and greater volume reductions for almost all procedure types. Centers in Central America and Mexico reported the largest procedure reductions (47 % reduction) compared to the Caribbean (15 %), and South America (14 %, p = 0.01), and this LATAM region was a significant predictor of lower procedure recovery in multivariable regression. More LATAM centers reported reduced salaries and increased layoffs of clinical staff compared to RoW, and LATAM respondents estimated that half of physician and non-physician staff experienced excess psychological stress related to the pandemic, compared to 25 % and 30 % in RoW (p

BackgroundCardiac systolic dysfunction is a poor prognostic marker in light-chain (AL) cardiomyopathy, a primary interstitial disorder; however, its pathogenesis is poorly understood.PurposeThis study aims to analyze the effects of extracellular volume (ECV) expansion, a surrogate marker of amyloid burden on myocardial blood flow (MBF), myocardial work efficiency (MWE), and left ventricular (LV) systolic dysfunction in AL amyloidosis.MethodsSubjects with biopsy-proven AL amyloidosis were prospectively enrolled (April 2016–June 2021; Clinicaltrials.gov ID NCT02641145) and underwent cardiac magnetic resonance imaging (MRI) to quantify rest MBF by perfusion imaging, LV ejection fraction (LVEF) by cine MRI, and ECV by pre- and post-contrast T1 mapping. The MWE was estimated as external cardiac work from the stroke volume and mean arterial pressure normalized to the LV myocardial mass.ResultsRest MBF in 92 subjects (62 ± 8 years, 52 men) with AL amyloidosis averaged 0.87 ± 0.21 ml/min/g and correlated with MWE (r = 0.42; p

BackgroundMachine learning (ML) models can improve prediction of major adverse cardiovascular events (MACE), but in clinical practice some values may be missing. We evaluated the influence of missing values in ML models for patient-specific prediction of MACE risk.MethodsWe included 20,179 patients from the multicenter REFINE SPECT registry with MACE follow-up data. We evaluated seven methods for handling missing values: 1) removal of variables with missing values (ML-Remove), 2) imputation with median and unique category for continuous and categorical variables, respectively (ML-Traditional), 3) unique category for missing variables (ML-Unique), 4) cluster-based imputation (ML-Cluster), 5) regression-based imputation (ML-Regression), 6) missRanger imputation (ML-MR), and 7) multiple imputation (ML-MICE). We trained ML models with full data and simulated missing values in testing patients. Prediction performance was evaluated using area under the receiver-operating characteristic curve (AUC) and compared with a model without missing values (ML-All), expert visual diagnosis and total perfusion deficit (TPD).ResultsDuring mean follow-up of 4.7 ± 1.5 years, 3,541 patients experienced at least one MACE (3.7% annualized risk). ML-All (reference model-no missing values) had AUC 0.799 for MACE risk prediction. All seven models with missing values had lower AUC (ML-Remove: 0.778, ML-MICE: 0.774, ML-Cluster: 0.771, ML-Traditional: 0.771, ML-Regression: 0.770, ML-MR: 0.766, and ML-Unique: 0.766; p

BackgroundSingle photon emission computed tomography (SPECT) has limited ability to identify multivessel and microvascular coronary artery disease. Gamma cameras with cadmium zinc telluride detectors allow the quantification of absolute myocardial blood flow (MBF) and myocardial flow reserve (MFR). However, evidence of its accuracy is limited, and of its reproducibility is lacking. We aimed to validate 99mTc-sestamibi SPECT MBF and MFR using standard and spline-fitted reconstruction algorithms compared with 13N-ammonia positron emission tomography in a cohort of patients with known or suspected coronary artery disease and to evaluate the reproducibility of this technique.MethodsAccuracy was assessed in 34 participants who underwent dynamic 99mTc-sestamibi SPECT and 13N-ammonia positron emission tomography and reproducibility in 14 participants who underwent 2 99mTc-sestamibi SPECT studies, all within 2 weeks. A rest/pharmacological stress single-day SPECT protocol was performed. SPECT images were reconstructed using a standard ordered subset expectation maximization (OSEM) algorithm with (N=21) and without (N=30) application of spline fitting. SPECT MBF was quantified using a net retention kinetic model' and MFR was derived as the stress/rest MBF ratio.ResultsSPECT global MBF with splines showed good correlation with 13N-ammonia positron emission tomography (r=0.81, P0.05 for all).ConclusionsMBF and MFR quantification using 99mTc-sestamibi cadmium zinc telluride SPECT with spatiotemporal spline fitting improved the correlation with 13N-ammonia positron emission tomography flow estimates and test/retest reproducibility. The use of splines may represent an important step toward the standardization of SPECT flow estimation.

BACKGROUND: The extent to which health care systems have adapted to the COVID-19 pandemic to provide necessary cardiac diagnostic services is unknown. OBJECTIVES: The aim of this study was to determine the impact of the pandemic on cardiac testing practices, volumes and types of diagnostic services, and perceived psychological stress to health care providers worldwide. METHODS: The International Atomic Energy Agency conducted a worldwide survey assessing alterations from baseline in cardiovascular diagnostic care at the pandemics onset and 1 year later. Multivariable regression was used to determine factors associated with procedure volume recovery. RESULTS: Surveys were submitted from 669 centers in 107 countries. Worldwide reduction in cardiac procedure volumes of 64% from March 2019 to April 2020 recovered by April 2021 in high- and upper middle-income countries (recovery rates of 108% and 99%) but remained depressed in lower middle- and low-income countries (46% and 30% recovery). Although stress testing was used 12% less frequently in 2021 than in 2019, coronary computed tomographic angiography was used 14% more, a trend also seen for other advanced cardiac imaging modalities (positron emission tomography and magnetic resonance; 22%-25% increases). Pandemic-related psychological stress was estimated to have affected nearly 40% of staff, impacting patient care at 78% of sites. In multivariable regression, only lower-income status and physicians psychological stress were significant in predicting recovery of cardiac testing. CONCLUSIONS: Cardiac diagnostic testing has yet to recover to prepandemic levels in lower-income countries. Worldwide, the decrease in standard stress testing is offset by greater use of advanced cardiac imaging modalities. Pandemic-related psychological stress among providers is widespread and associated with poor recovery of cardiac testing.

Summary: Background: Myocardial perfusion imaging (MPI) is one of the most common cardiac scans and is used for diagnosis of coronary artery disease and assessment of cardiovascular risk. However, the large majority of MPI patients have normal results. We evaluated whether unsupervised machine learning could identify unique phenotypes among patients with normal scans and whether those phenotypes were associated with risk of death or myocardial infarction. Methods: Patients from a large international multicenter MPI registry (10 sites) with normal perfusion by expert visual interpretation were included in this cohort analysis. The training population included 9849 patients, and external testing population 12,528 patients. Unsupervised cluster analysis was performed, with separate training and external testing cohorts, to identify clusters, with four distinct phenotypes. We evaluated the clinical and imaging features of clusters and their associations with death or myocardial infarction. Findings: Patients in Clusters 1 and 2 almost exclusively underwent exercise stress, while patients in Clusters 3 and 4 mostly required pharmacologic stress. In external testing, the risk for Cluster 4 patients (20.2% of population, unadjusted hazard ratio [HR] 6.17, 95% confidence interval [CI] 4.64–8.20) was higher than the risk associated with pharmacologic stress (HR 3.03, 95% CI 2.53–3.63), or previous myocardial infarction (HR 1.82, 95% CI 1.40–2.36). Interpretation: Unsupervised learning identified four distinct phenotypes of patients with normal perfusion scans, with a significant proportion of patients at very high risk of myocardial infarction or death. Our results suggest a potential role for patient phenotyping to improve risk stratification of patients with normal imaging results. Funding: This work was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R35HL161195 to PS]. The REFINE SPECT database was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R01HL089765 to PS]. MCW was supported by the British Heart Foundation [FS/ICRF/20/26002].

BackgroundThe coronavirus disease-2019 (COVID-19) pandemic significantly affected management of cardiovascular disease around the world. The effect of the pandemic on volume of cardiovascular diagnostic procedures is not known.ObjectivesThis study sought to evaluate the effects of the early phase of the COVID-19 pandemic on cardiovascular diagnostic procedures and safety practices in Asia.MethodsThe International Atomic Energy Agency conducted a worldwide survey to assess changes in cardiovascular procedure volume and safety practices caused by COVID-19. Testing volumes were reported for March 2020 and April 2020 and were compared to those from March 2019. Data from 180 centers across 33 Asian countries were grouped into 4 subregions for comparison.ResultsProcedure volumes decreased by 47% from March 2019 to March 2020, showing recovery from March 2020 to April 2020 in Eastern Asia, particularly in China. The majority of centers cancelled outpatient activities and increased time per study. Practice changes included implementing physical distancing and restricting visitors. Although COVID testing was not commonly performed, it was conducted in one-third of facilities in Eastern Asia. The most severe reductions in procedure volumes were observed in lower-income countries, where volumes decreased 81% from March 2019 to April 2020.ConclusionsThe COVID-19 pandemic in Asia caused significant reductions in cardiovascular diagnostic procedures, particularly in low-income countries. Further studies on effects of COVID-19 on cardiovascular outcomes and changes in care delivery are warranted.

ObjectivesThis study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-U.S. institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic.BackgroundThe COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality.MethodsData were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States.ResultsReductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p

We aimed to explore the impact of the COVID-19 pandemic on cardiac diagnostic testing and practice and to assess its impact in different regions in Europe. The online survey organised by the International Atomic Energy Agency Division of Human Health collected information on changes in cardiac imaging procedural volumes between March 2019 and March/April 2020. Data were collected from 909 centres in 108 countries. Centres in Northern and Southern Europe were more likely to cancel all outpatient activities compared with Western and Eastern Europe. There was a greater reduction in total procedure volumes in Europe compared with the rest of the world in March 2020 (45% vs 41%, p=0.003), with a more marked reduction in Southern Europe (58%), but by April 2020 this was similar in Europe and the rest of the world (69% vs 63%, p=0.261). Regional variations were apparent between imaging modalities, but the largest reductions were in Southern Europe for nearly all modalities. In March 2020, location in Southern Europe was the only independent predictor of the reduction in procedure volume. However, in April 2020, lower gross domestic product and higher COVID-19 deaths were the only independent predictors. The first wave of the COVID-19 pandemic had a significant impact on care of patients with cardiac disease, with substantial regional variations in Europe. This has potential long-term implications for patients and plans are required to enable the diagnosis of non-COVID-19 conditions during the ongoing pandemic.

Abstract Standard clinical interpretation of myocardial perfusion imaging (MPI) has proven prognostic value for predicting major adverse cardiovascular events (MACE). However, personalizing predictions to a specific event type and time interval is more challenging. We demonstrate an explainable deep learning model that predicts the time-specific risk separately for all-cause death, acute coronary syndrome (ACS), and revascularization directly from MPI and 15 clinical features. We train and test the model internally using 10-fold hold-out cross-validation (n = 20,418) and externally validate it in three separate sites (n = 13,988) with MACE follow-ups for a median of 3.1 years (interquartile range [IQR]: 1.6, 3.6). We evaluate the model using the cumulative dynamic area under receiver operating curve (cAUC). The best model performance in the external cohort is observed for short-term prediction – in the first six months after the scan, mean cAUC for ACS and all-cause death reaches 0.76 (95% confidence interval [CI]: 0.75, 0.77) and 0.78 (95% CI: 0.78, 0.79), respectively. The model outperforms conventional perfusion abnormality measures at all time points for the prediction of death in both internal and external validations, with improvement increasing gradually over time. Individualized patient explanations are visualized using waterfall plots, which highlight the contribution degree and direction for each feature. This approach allows the derivation of individual event probability as a function of time as well as patient- and event-specific risk explanations that may help draw attention to modifiable risk factors. Such a method could help present post-scan risk assessments to the patient and foster shared decision-making.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has adversely affected diagnosis and treatment of noncommunicable diseases. Its effects on delivery of diagnostic care for cardiovascular disease, which remains the leading cause of death worldwide, have not been quantified.ObjectivesThe study sought to assess COVID-19's impact on global cardiovascular diagnostic procedural volumes and safety practices.MethodsThe International Atomic Energy Agency conducted a worldwide survey assessing alterations in cardiovascular procedure volumes and safety practices resulting from COVID-19. Noninvasive and invasive cardiac testing volumes were obtained from participating sites for March and April 2020 and compared with those from March 2019. Availability of personal protective equipment and pandemic-related testing practice changes were ascertained.ResultsSurveys were submitted from 909 inpatient and outpatient centers performing cardiac diagnostic procedures, in 108 countries. Procedure volumes decreased 42% from March 2019 to March 2020, and 64% from March 2019 to April 2020. Transthoracic echocardiography decreased by 59%, transesophageal echocardiography 76%, and stress tests 78%, which varied between stress modalities. Coronary angiography (invasive or computed tomography) decreased 55% (p

ObjectivePrevalence and prognostic impact of cardiovascular disease differ between patients with or without diabetes. We aimed to explore differences in the prevalence and prognosis of myocardial ischemia by automated quantification of total perfusion deficit (TPD) among patients with and without diabetes.Research design and methodsOf 20,418 individuals who underwent single-photon emission computed tomography myocardial perfusion imaging, 2,951 patients with diabetes were matched to 2,951 patients without diabetes based on risk factors using propensity score. TPD was categorized as TPD = 0%, 0% < TPD < 1%, 1% ≤ TPD < 5%, 5% ≤ TPD ≤ 10%, and TPD >10%. Major adverse cardiovascular events (MACE) were defined as a composite of all-cause mortality, myocardial infarction, unstable angina, or late revascularization.ResultsMACE risk was increased in patients with diabetes compared with patients without diabetes at each level of TPD above 0 (P < 0.001 for interaction). In patients with TPD >10%, patients with diabetes had greater than twice the MACE risk compared with patients without diabetes (annualized MACE rate 9.4 [95% CI 6.7-11.6] and 3.9 [95% CI 2.8-5.6], respectively, P < 0.001). Patients with diabetes with even very minimal TPD (0% < TPD < 1%) experienced a higher risk for MACE than those with 0% TPD (hazard ratio 2.05 [95% CI 1.21-3.47], P = 0.007). Patients with diabetes with a TPD of 0.5% had a similar MACE risk as patients without diabetes with a TPD of 8%.ConclusionsFor every level of TPD >0%, even a very minimal deficit of 0% < TPD < 1%, the MACE risk was higher in the patients with diabetes compared with patients without diabetes. Patients with diabetes with minimal ischemia had comparable MACE risk as patients without diabetes with significant ischemia.

Cardiac dysfunction is the most frequent cause of morbidity and mortality in amyloid light chain (AL) amyloidosis caused by a clonal immunoglobulin light chain (LC). Previously published transgenic animal models of AL amyloidosis have not recapitulated the key phenotype of cardiac dysfunction seen in AL amyloidosis, which has limited our understanding of the disease mechanisms in vivo, as well as the development of targeted AL therapeutics. We have developed a transgenic zebrafish model in which a λ LC derived from a patient with AL amyloidosis is conditionally expressed in the liver under the control of the Gal4 upstream activation sequence enhancer system. Circulating LC levels of 125 µg/ml in these transgenic zebrafish are comparable to median pathological serum LC levels. Functional analysis links abnormal contractile function with evidence of cellular and molecular proteotoxicity in the heart, including increased cell death and autophagy. However, despite pathological and functional phenotypes analogous to human AL, the lifespan of the transgenic fish is comparable to control fish without the expressed AL-LC transgene. Nuclear labeling experiments suggest increased cardiac proliferation in the transgenic fish, which can be counteracted by treatment with a small molecule proliferation inhibitor leading to increased zebrafish mortality because of cardiac apoptosis and functional deterioration. This transgenic zebrafish model provides a platform to study underlying AL disease mechanisms in vivo further. NEW & NOTEWORTHY Heart failure is a major cause of mortality in amyloid light (AL) amyloidosis, yet it has been difficult to model in animals. We report the generation of a transgenic zebrafish model for AL amyloidosis with pathological concentration of circulating human light chain protein that results in cardiac dysfunction. The light chain toxicity triggers regeneration in the zebrafish heart resulting in functional compensation early in life, but with age develops into cardiac dysfunction.

Combined analysis of SPECT myocardial perfusion imaging (MPI) performed with a solid-state camera on patients in 2 positions (semiupright, supine) is routinely used to mitigate attenuation artifacts. We evaluated the prediction of obstructive disease from combined analysis of semiupright and supine stress MPI by deep learning (DL) as compared with standard combined total perfusion deficit (TPD). Methods: 1,160 patients without known coronary artery disease (64% male) were studied. Patients underwent stress 99mTc-sestamibi MPI with new-generation solid-state SPECT scanners in 4 different centers. All patients had on-site clinical reads and invasive coronary angiography correlations within 6 mo of MPI. Obstructive disease was defined as at least 70% narrowing of the 3 major coronary arteries and at least 50% for the left main coronary artery. Images were quantified at Cedars-Sinai. The left ventricular myocardium was segmented using standard clinical nuclear cardiology software. The contour placement was verified by an experienced technologist. Combined stress TPD was computed using sex- and camera-specific normal limits. DL was trained using polar distributions of normalized radiotracer counts, hypoperfusion defects, and hypoperfusion severities and was evaluated for prediction of obstructive disease in a novel leave-one-center-out cross-validation procedure equivalent to external validation. During the validation procedure, 4 DL models were trained using data from 3 centers and then evaluated on the 1 center left aside. Predictions for each center were merged to have an overall estimation of the multicenter performance. Results: 718 (62%) patients and 1,272 of 3,480 (37%) arteries had obstructive disease. The area under the receiver operating characteristics curve for prediction of disease on a per-patient and per-vessel basis by DL was higher than for combined TPD (per-patient, 0.81 vs. 0.78; per-vessel, 0.77 vs. 0.73; P < 0.001). With the DL cutoff set to exhibit the same specificity as the standard cutoff for combined TPD, per-patient sensitivity improved from 61.8% (TPD) to 65.6% (DL) (P < 0.05), and per-vessel sensitivity improved from 54.6% (TPD) to 59.1% (DL) (P < 0.01). With the threshold matched to the specificity of a normal clinical read (56.3%), DL had a sensitivity of 84.8%, versus 82.6% for an on-site clinical read (P = 0.3). Conclusion: DL improves automatic interpretation of MPI as compared with current quantitative methods.